Overview

Dataset statistics

Number of variables44
Number of observations20336
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 MiB
Average record size in memory352.0 B

Variable types

Numeric43
Categorical1

Alerts

EtCO2 has constant value "0" Constant
HR is highly correlated with O2Sat and 24 other fieldsHigh correlation
O2Sat is highly correlated with HR and 23 other fieldsHigh correlation
Temp is highly correlated with HR and 21 other fieldsHigh correlation
SBP is highly correlated with HR and 15 other fieldsHigh correlation
MAP is highly correlated with HR and 24 other fieldsHigh correlation
DBP is highly correlated with O2Sat and 12 other fieldsHigh correlation
Resp is highly correlated with HR and 23 other fieldsHigh correlation
BaseExcess is highly correlated with Temp and 10 other fieldsHigh correlation
HCO3 is highly correlated with HR and 22 other fieldsHigh correlation
FiO2 is highly correlated with DBP and 4 other fieldsHigh correlation
pH is highly correlated with Temp and 10 other fieldsHigh correlation
PaCO2 is highly correlated with Temp and 10 other fieldsHigh correlation
SaO2 is highly correlated with DBP and 4 other fieldsHigh correlation
AST is highly correlated with Alkalinephos and 1 other fieldsHigh correlation
BUN is highly correlated with HR and 22 other fieldsHigh correlation
Alkalinephos is highly correlated with AST and 1 other fieldsHigh correlation
Calcium is highly correlated with HR and 15 other fieldsHigh correlation
Chloride is highly correlated with HR and 22 other fieldsHigh correlation
Creatinine is highly correlated with HR and 25 other fieldsHigh correlation
Glucose is highly correlated with HR and 21 other fieldsHigh correlation
Lactate is highly correlated with BaseExcess and 2 other fieldsHigh correlation
Magnesium is highly correlated with HR and 22 other fieldsHigh correlation
Phosphate is highly correlated with HR and 17 other fieldsHigh correlation
Potassium is highly correlated with HR and 25 other fieldsHigh correlation
Bilirubin_total is highly correlated with AST and 1 other fieldsHigh correlation
Hct is highly correlated with HR and 18 other fieldsHigh correlation
Hgb is highly correlated with HR and 25 other fieldsHigh correlation
PTT is highly correlated with Creatinine and 1 other fieldsHigh correlation
WBC is highly correlated with HR and 22 other fieldsHigh correlation
Platelets is highly correlated with HR and 25 other fieldsHigh correlation
Age is highly correlated with HR and 22 other fieldsHigh correlation
Gender is highly correlated with HR and 22 other fieldsHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
HospAdmTime is highly correlated with HR and 22 other fieldsHigh correlation
ICULOS is highly correlated with HR and 22 other fieldsHigh correlation
SepsisLabel is highly correlated with HR and 22 other fieldsHigh correlation
Sepsis is highly correlated with HR and 22 other fieldsHigh correlation
Hours is highly correlated with HR and 22 other fieldsHigh correlation
HR is highly correlated with O2Sat and 28 other fieldsHigh correlation
O2Sat is highly correlated with HR and 28 other fieldsHigh correlation
Temp is highly correlated with HR and 23 other fieldsHigh correlation
SBP is highly correlated with HR and 29 other fieldsHigh correlation
MAP is highly correlated with HR and 29 other fieldsHigh correlation
DBP is highly correlated with HR and 27 other fieldsHigh correlation
Resp is highly correlated with HR and 28 other fieldsHigh correlation
BaseExcess is highly correlated with HR and 22 other fieldsHigh correlation
HCO3 is highly correlated with HR and 30 other fieldsHigh correlation
FiO2 is highly correlated with HR and 24 other fieldsHigh correlation
pH is highly correlated with HR and 22 other fieldsHigh correlation
PaCO2 is highly correlated with HR and 17 other fieldsHigh correlation
SaO2 is highly correlated with Temp and 6 other fieldsHigh correlation
AST is highly correlated with HCO3 and 11 other fieldsHigh correlation
BUN is highly correlated with HR and 30 other fieldsHigh correlation
Alkalinephos is highly correlated with HCO3 and 11 other fieldsHigh correlation
Calcium is highly correlated with HR and 22 other fieldsHigh correlation
Chloride is highly correlated with HR and 28 other fieldsHigh correlation
Creatinine is highly correlated with HR and 33 other fieldsHigh correlation
Glucose is highly correlated with Temp and 12 other fieldsHigh correlation
Lactate is highly correlated with BaseExcess and 10 other fieldsHigh correlation
Magnesium is highly correlated with HR and 30 other fieldsHigh correlation
Phosphate is highly correlated with HR and 24 other fieldsHigh correlation
Potassium is highly correlated with HR and 32 other fieldsHigh correlation
Bilirubin_total is highly correlated with AST and 6 other fieldsHigh correlation
Hct is highly correlated with HR and 28 other fieldsHigh correlation
Hgb is highly correlated with HR and 35 other fieldsHigh correlation
PTT is highly correlated with HCO3 and 20 other fieldsHigh correlation
WBC is highly correlated with HR and 31 other fieldsHigh correlation
Fibrinogen is highly correlated with AST and 6 other fieldsHigh correlation
Platelets is highly correlated with HR and 34 other fieldsHigh correlation
Age is highly correlated with HR and 26 other fieldsHigh correlation
Gender is highly correlated with HR and 26 other fieldsHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
HospAdmTime is highly correlated with HR and 26 other fieldsHigh correlation
ICULOS is highly correlated with HR and 26 other fieldsHigh correlation
SepsisLabel is highly correlated with HR and 26 other fieldsHigh correlation
Sepsis is highly correlated with HR and 26 other fieldsHigh correlation
Hours is highly correlated with HR and 26 other fieldsHigh correlation
HR is highly correlated with O2Sat and 13 other fieldsHigh correlation
O2Sat is highly correlated with HR and 12 other fieldsHigh correlation
Temp is highly correlated with HR and 4 other fieldsHigh correlation
SBP is highly correlated with HR and 10 other fieldsHigh correlation
MAP is highly correlated with HR and 13 other fieldsHigh correlation
DBP is highly correlated with BaseExcess and 2 other fieldsHigh correlation
Resp is highly correlated with HR and 12 other fieldsHigh correlation
BaseExcess is highly correlated with DBP and 6 other fieldsHigh correlation
HCO3 is highly correlated with BUN and 10 other fieldsHigh correlation
FiO2 is highly correlated with BaseExcess and 2 other fieldsHigh correlation
pH is highly correlated with DBP and 6 other fieldsHigh correlation
PaCO2 is highly correlated with DBP and 6 other fieldsHigh correlation
SaO2 is highly correlated with BaseExcess and 2 other fieldsHigh correlation
AST is highly correlated with Alkalinephos and 1 other fieldsHigh correlation
BUN is highly correlated with HCO3 and 10 other fieldsHigh correlation
Alkalinephos is highly correlated with AST and 1 other fieldsHigh correlation
Calcium is highly correlated with HCO3 and 5 other fieldsHigh correlation
Chloride is highly correlated with HCO3 and 10 other fieldsHigh correlation
Creatinine is highly correlated with HR and 21 other fieldsHigh correlation
Glucose is highly correlated with Temp and 8 other fieldsHigh correlation
Lactate is highly correlated with BaseExcess and 2 other fieldsHigh correlation
Magnesium is highly correlated with HCO3 and 9 other fieldsHigh correlation
Phosphate is highly correlated with HCO3 and 5 other fieldsHigh correlation
Potassium is highly correlated with HCO3 and 9 other fieldsHigh correlation
Bilirubin_total is highly correlated with AST and 1 other fieldsHigh correlation
Hct is highly correlated with HCO3 and 7 other fieldsHigh correlation
Hgb is highly correlated with HCO3 and 9 other fieldsHigh correlation
PTT is highly correlated with PlateletsHigh correlation
WBC is highly correlated with HCO3 and 8 other fieldsHigh correlation
Platelets is highly correlated with HR and 19 other fieldsHigh correlation
Age is highly correlated with HR and 12 other fieldsHigh correlation
Gender is highly correlated with HR and 12 other fieldsHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
HospAdmTime is highly correlated with HR and 12 other fieldsHigh correlation
ICULOS is highly correlated with HR and 12 other fieldsHigh correlation
SepsisLabel is highly correlated with HR and 12 other fieldsHigh correlation
Sepsis is highly correlated with HR and 12 other fieldsHigh correlation
Hours is highly correlated with HR and 12 other fieldsHigh correlation
Fibrinogen is highly skewed (γ1 = 20.20727704) Skewed
PatientID has unique values Unique
Temp has 235 (1.2%) zeros Zeros
SBP has 258 (1.3%) zeros Zeros
DBP has 7384 (36.3%) zeros Zeros
BaseExcess has 7684 (37.8%) zeros Zeros
HCO3 has 535 (2.6%) zeros Zeros
FiO2 has 8349 (41.1%) zeros Zeros
pH has 7155 (35.2%) zeros Zeros
PaCO2 has 7759 (38.2%) zeros Zeros
SaO2 has 12373 (60.8%) zeros Zeros
AST has 14443 (71.0%) zeros Zeros
BUN has 427 (2.1%) zeros Zeros
Alkalinephos has 14633 (72.0%) zeros Zeros
Calcium has 3789 (18.6%) zeros Zeros
Chloride has 542 (2.7%) zeros Zeros
Creatinine has 461 (2.3%) zeros Zeros
Bilirubin_direct has 19750 (97.1%) zeros Zeros
Glucose has 407 (2.0%) zeros Zeros
Lactate has 12603 (62.0%) zeros Zeros
Magnesium has 1388 (6.8%) zeros Zeros
Phosphate has 3650 (17.9%) zeros Zeros
Potassium has 433 (2.1%) zeros Zeros
Bilirubin_total has 14566 (71.6%) zeros Zeros
TroponinI has 19847 (97.6%) zeros Zeros
Hct has 364 (1.8%) zeros Zeros
Hgb has 507 (2.5%) zeros Zeros
PTT has 4496 (22.1%) zeros Zeros
WBC has 625 (3.1%) zeros Zeros
Fibrinogen has 17769 (87.4%) zeros Zeros
Platelets has 585 (2.9%) zeros Zeros
Unit1 has 9522 (46.8%) zeros Zeros
Unit2 has 9522 (46.8%) zeros Zeros

Reproduction

Analysis started2021-11-29 10:22:09.180544
Analysis finished2021-11-29 10:22:25.001031
Duration15.82 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

UNIQUE

Distinct20336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10173.60651
Minimum1
Maximum20643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:25.050424image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1017.75
Q15084.75
median10168.5
Q315252.25
95-th percentile19320.25
Maximum20643
Range20642
Interquartile range (IQR)10167.5

Descriptive statistics

Standard deviation5879.461518
Coefficient of variation (CV)0.5779132024
Kurtosis-1.192915145
Mean10173.60651
Median Absolute Deviation (MAD)5084
Skewness0.005160825078
Sum206890462
Variance34568067.75
MonotonicityStrictly increasing
2021-11-29T11:22:25.225914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
< 0.1%
135561
 
< 0.1%
135631
 
< 0.1%
135621
 
< 0.1%
135611
 
< 0.1%
135601
 
< 0.1%
135591
 
< 0.1%
135581
 
< 0.1%
135571
 
< 0.1%
135551
 
< 0.1%
Other values (20326)20326
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
206431
< 0.1%
206421
< 0.1%
206411
< 0.1%
206401
< 0.1%
206391
< 0.1%
206381
< 0.1%
206371
< 0.1%
206361
< 0.1%
206351
< 0.1%
206341
< 0.1%

HR
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct231
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.84903619
Minimum0
Maximum333
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:25.328684image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q123
median35
Q344
95-th percentile55
Maximum333
Range333
Interquartile range (IQR)21

Descriptive statistics

Standard deviation21.52956412
Coefficient of variation (CV)0.6005618675
Kurtosis39.45265762
Mean35.84903619
Median Absolute Deviation (MAD)11
Skewness4.638669822
Sum729026
Variance463.5221314
MonotonicityNot monotonic
2021-11-29T11:22:25.427732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35660
 
3.2%
38638
 
3.1%
36634
 
3.1%
37619
 
3.0%
39588
 
2.9%
42581
 
2.9%
40570
 
2.8%
41561
 
2.8%
44551
 
2.7%
22533
 
2.6%
Other values (221)14401
70.8%
ValueCountFrequency (%)
01
 
< 0.1%
15
 
< 0.1%
26
 
< 0.1%
39
 
< 0.1%
417
 
0.1%
522
 
0.1%
639
 
0.2%
7110
0.5%
8131
0.6%
9127
0.6%
ValueCountFrequency (%)
3331
< 0.1%
3281
< 0.1%
3211
< 0.1%
3111
< 0.1%
3101
< 0.1%
3052
< 0.1%
3032
< 0.1%
3011
< 0.1%
2981
< 0.1%
2851
< 0.1%

O2Sat
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct231
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.18253344
Minimum0
Maximum331
Zeros12
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:25.531604image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q121
median34
Q343
95-th percentile55
Maximum331
Range331
Interquartile range (IQR)22

Descriptive statistics

Standard deviation21.45574231
Coefficient of variation (CV)0.6276814546
Kurtosis37.24152281
Mean34.18253344
Median Absolute Deviation (MAD)11
Skewness4.477267879
Sum695136
Variance460.3488781
MonotonicityNot monotonic
2021-11-29T11:22:25.629276image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35616
 
3.0%
36613
 
3.0%
38583
 
2.9%
39564
 
2.8%
40559
 
2.7%
37558
 
2.7%
41547
 
2.7%
22536
 
2.6%
42534
 
2.6%
33521
 
2.6%
Other values (221)14705
72.3%
ValueCountFrequency (%)
012
 
0.1%
110
 
< 0.1%
226
 
0.1%
339
 
0.2%
438
 
0.2%
556
 
0.3%
678
0.4%
7136
0.7%
8182
0.9%
9188
0.9%
ValueCountFrequency (%)
3311
< 0.1%
3281
< 0.1%
3231
< 0.1%
3121
< 0.1%
3081
< 0.1%
3011
< 0.1%
2981
< 0.1%
2951
< 0.1%
2821
< 0.1%
2811
< 0.1%

Temp
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct121
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.12455744
Minimum0
Maximum282
Zeros235
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:25.731522image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16
median10
Q315
95-th percentile35
Maximum282
Range282
Interquartile range (IQR)9

Descriptive statistics

Standard deviation11.50944598
Coefficient of variation (CV)0.8769397396
Kurtosis38.2796727
Mean13.12455744
Median Absolute Deviation (MAD)4
Skewness3.969228021
Sum266901
Variance132.4673467
MonotonicityNot monotonic
2021-11-29T11:22:25.827727image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101456
 
7.2%
91372
 
6.7%
111349
 
6.6%
51246
 
6.1%
81176
 
5.8%
61171
 
5.8%
121166
 
5.7%
71164
 
5.7%
41147
 
5.6%
13990
 
4.9%
Other values (111)8099
39.8%
ValueCountFrequency (%)
0235
 
1.2%
1240
 
1.2%
2420
 
2.1%
3785
3.9%
41147
5.6%
51246
6.1%
61171
5.8%
71164
5.7%
81176
5.8%
91372
6.7%
ValueCountFrequency (%)
2821
< 0.1%
2161
< 0.1%
1601
< 0.1%
1531
< 0.1%
1461
< 0.1%
1441
< 0.1%
1421
< 0.1%
1411
< 0.1%
1401
< 0.1%
1371
< 0.1%

SBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct227
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.94718725
Minimum0
Maximum330
Zeros258
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:25.930845image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q120
median33
Q342
95-th percentile54
Maximum330
Range330
Interquartile range (IQR)22

Descriptive statistics

Standard deviation21.25755427
Coefficient of variation (CV)0.6452008817
Kurtosis37.04566798
Mean32.94718725
Median Absolute Deviation (MAD)11
Skewness4.300711256
Sum670014
Variance451.8836134
MonotonicityNot monotonic
2021-11-29T11:22:26.030412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35615
 
3.0%
19584
 
2.9%
36581
 
2.9%
37573
 
2.8%
38570
 
2.8%
18559
 
2.7%
21556
 
2.7%
34535
 
2.6%
22520
 
2.6%
39518
 
2.5%
Other values (217)14725
72.4%
ValueCountFrequency (%)
0258
1.3%
160
 
0.3%
252
 
0.3%
364
 
0.3%
457
 
0.3%
557
 
0.3%
658
 
0.3%
7127
0.6%
8168
0.8%
9162
0.8%
ValueCountFrequency (%)
3301
< 0.1%
3211
< 0.1%
3161
< 0.1%
3101
< 0.1%
3081
< 0.1%
3051
< 0.1%
2991
< 0.1%
2981
< 0.1%
2962
< 0.1%
2921
< 0.1%

MAP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct231
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.88183517
Minimum0
Maximum329
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:26.135487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q122
median34
Q343
95-th percentile55
Maximum329
Range329
Interquartile range (IQR)21

Descriptive statistics

Standard deviation21.41701243
Coefficient of variation (CV)0.6139875476
Kurtosis38.87119575
Mean34.88183517
Median Absolute Deviation (MAD)11
Skewness4.597441044
Sum709357
Variance458.6884214
MonotonicityNot monotonic
2021-11-29T11:22:26.234435image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35679
 
3.3%
37623
 
3.1%
36617
 
3.0%
38603
 
3.0%
41566
 
2.8%
39547
 
2.7%
40541
 
2.7%
34535
 
2.6%
44531
 
2.6%
42518
 
2.5%
Other values (221)14576
71.7%
ValueCountFrequency (%)
02
 
< 0.1%
18
 
< 0.1%
28
 
< 0.1%
316
 
0.1%
428
 
0.1%
537
 
0.2%
649
 
0.2%
7126
0.6%
8154
0.8%
9157
0.8%
ValueCountFrequency (%)
3291
< 0.1%
3281
< 0.1%
3191
< 0.1%
3091
< 0.1%
3081
< 0.1%
3051
< 0.1%
3031
< 0.1%
2991
< 0.1%
2961
< 0.1%
2941
< 0.1%

DBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct211
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.15725806
Minimum0
Maximum316
Zeros7384
Zeros (%)36.3%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:26.339181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median18
Q335
95-th percentile51
Maximum316
Range316
Interquartile range (IQR)35

Descriptive statistics

Standard deviation23.59270733
Coefficient of variation (CV)1.17043237
Kurtosis19.55864092
Mean20.15725806
Median Absolute Deviation (MAD)18
Skewness2.906221689
Sum409918
Variance556.6158391
MonotonicityNot monotonic
2021-11-29T11:22:26.438159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
07384
36.3%
21458
 
2.3%
20450
 
2.2%
19434
 
2.1%
18385
 
1.9%
22381
 
1.9%
23333
 
1.6%
17332
 
1.6%
36330
 
1.6%
38325
 
1.6%
Other values (201)9524
46.8%
ValueCountFrequency (%)
07384
36.3%
1179
 
0.9%
2148
 
0.7%
3132
 
0.6%
4102
 
0.5%
584
 
0.4%
656
 
0.3%
791
 
0.4%
8119
 
0.6%
9106
 
0.5%
ValueCountFrequency (%)
3161
< 0.1%
3131
< 0.1%
3081
< 0.1%
2921
< 0.1%
2842
< 0.1%
2731
< 0.1%
2641
< 0.1%
2611
< 0.1%
2591
< 0.1%
2521
< 0.1%

Resp
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct233
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.05886113
Minimum0
Maximum323
Zeros28
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:26.616573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q122
median35
Q344
95-th percentile55
Maximum323
Range323
Interquartile range (IQR)22

Descriptive statistics

Standard deviation21.56457192
Coefficient of variation (CV)0.6150961902
Kurtosis37.51952272
Mean35.05886113
Median Absolute Deviation (MAD)11
Skewness4.481368744
Sum712957
Variance465.0307619
MonotonicityNot monotonic
2021-11-29T11:22:26.713935image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35652
 
3.2%
38629
 
3.1%
37623
 
3.1%
40597
 
2.9%
36592
 
2.9%
39546
 
2.7%
41546
 
2.7%
22537
 
2.6%
34525
 
2.6%
42519
 
2.6%
Other values (223)14570
71.6%
ValueCountFrequency (%)
028
 
0.1%
123
 
0.1%
224
 
0.1%
338
 
0.2%
438
 
0.2%
550
 
0.2%
658
 
0.3%
7116
0.6%
8156
0.8%
9144
0.7%
ValueCountFrequency (%)
3231
< 0.1%
3211
< 0.1%
3131
< 0.1%
3092
< 0.1%
3022
< 0.1%
2981
< 0.1%
2971
< 0.1%
2901
< 0.1%
2891
< 0.1%
2851
< 0.1%

EtCO2
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
0
20336 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20336
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
020336
100.0%

Length

2021-11-29T11:22:26.810619image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:22:26.863373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
020336
100.0%

Most occurring characters

ValueCountFrequency (%)
020336
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
020336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common20336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
020336
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
020336
100.0%

BaseExcess
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct66
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.050993312
Minimum0
Maximum112
Zeros7684
Zeros (%)37.8%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:26.922854image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q36
95-th percentile14
Maximum112
Range112
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.841451295
Coefficient of variation (CV)1.44197999
Kurtosis29.99984832
Mean4.050993312
Median Absolute Deviation (MAD)2
Skewness3.666042998
Sum82381
Variance34.12255323
MonotonicityNot monotonic
2021-11-29T11:22:27.018685image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
07684
37.8%
11728
 
8.5%
21495
 
7.4%
41331
 
6.5%
31252
 
6.2%
51135
 
5.6%
61003
 
4.9%
7797
 
3.9%
8753
 
3.7%
9564
 
2.8%
Other values (56)2594
 
12.8%
ValueCountFrequency (%)
07684
37.8%
11728
 
8.5%
21495
 
7.4%
31252
 
6.2%
41331
 
6.5%
51135
 
5.6%
61003
 
4.9%
7797
 
3.9%
8753
 
3.7%
9564
 
2.8%
ValueCountFrequency (%)
1121
< 0.1%
1041
< 0.1%
901
< 0.1%
851
< 0.1%
821
< 0.1%
811
< 0.1%
701
< 0.1%
681
< 0.1%
661
< 0.1%
652
< 0.1%

HCO3
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct43
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.12829465
Minimum0
Maximum85
Zeros535
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:27.116735image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q34
95-th percentile8
Maximum85
Range85
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.823853219
Coefficient of variation (CV)0.9026813439
Kurtosis67.56673567
Mean3.12829465
Median Absolute Deviation (MAD)1
Skewness5.265305102
Sum63617
Variance7.974147001
MonotonicityNot monotonic
2021-11-29T11:22:27.205387image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
26093
30.0%
34084
20.1%
13860
19.0%
42320
 
11.4%
51026
 
5.0%
6943
 
4.6%
0535
 
2.6%
8397
 
2.0%
7349
 
1.7%
9167
 
0.8%
Other values (33)562
 
2.8%
ValueCountFrequency (%)
0535
 
2.6%
13860
19.0%
26093
30.0%
34084
20.1%
42320
 
11.4%
51026
 
5.0%
6943
 
4.6%
7349
 
1.7%
8397
 
2.0%
9167
 
0.8%
ValueCountFrequency (%)
851
 
< 0.1%
491
 
< 0.1%
451
 
< 0.1%
431
 
< 0.1%
422
< 0.1%
391
 
< 0.1%
372
< 0.1%
363
< 0.1%
352
< 0.1%
331
 
< 0.1%

FiO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct92
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.515096381
Minimum0
Maximum133
Zeros8349
Zeros (%)41.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:27.298584image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q39
95-th percentile19
Maximum133
Range133
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.145376201
Coefficient of variation (CV)1.476923636
Kurtosis25.90001507
Mean5.515096381
Median Absolute Deviation (MAD)3
Skewness3.667877917
Sum112155
Variance66.34715345
MonotonicityNot monotonic
2021-11-29T11:22:27.400844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08349
41.1%
41022
 
5.0%
3995
 
4.9%
5916
 
4.5%
6881
 
4.3%
1791
 
3.9%
2785
 
3.9%
7752
 
3.7%
8698
 
3.4%
9610
 
3.0%
Other values (82)4537
22.3%
ValueCountFrequency (%)
08349
41.1%
1791
 
3.9%
2785
 
3.9%
3995
 
4.9%
41022
 
5.0%
5916
 
4.5%
6881
 
4.3%
7752
 
3.7%
8698
 
3.4%
9610
 
3.0%
ValueCountFrequency (%)
1331
< 0.1%
1161
< 0.1%
1121
< 0.1%
1111
< 0.1%
961
< 0.1%
921
< 0.1%
902
< 0.1%
892
< 0.1%
871
< 0.1%
861
< 0.1%

pH
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct70
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.455891031
Minimum0
Maximum124
Zeros7155
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:27.502417image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q37
95-th percentile15
Maximum124
Range124
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.130113003
Coefficient of variation (CV)1.375732252
Kurtosis29.28576252
Mean4.455891031
Median Absolute Deviation (MAD)2
Skewness3.501574226
Sum90615
Variance37.57828543
MonotonicityNot monotonic
2021-11-29T11:22:27.603922image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
07155
35.2%
11913
 
9.4%
21397
 
6.9%
41196
 
5.9%
51100
 
5.4%
31060
 
5.2%
61046
 
5.1%
7871
 
4.3%
8855
 
4.2%
9640
 
3.1%
Other values (60)3103
15.3%
ValueCountFrequency (%)
07155
35.2%
11913
 
9.4%
21397
 
6.9%
31060
 
5.2%
41196
 
5.9%
51100
 
5.4%
61046
 
5.1%
7871
 
4.3%
8855
 
4.2%
9640
 
3.1%
ValueCountFrequency (%)
1241
< 0.1%
1101
< 0.1%
921
< 0.1%
861
< 0.1%
841
< 0.1%
821
< 0.1%
741
< 0.1%
701
< 0.1%
681
< 0.1%
661
< 0.1%

PaCO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct52
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.407159717
Minimum0
Maximum112
Zeros7759
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:27.706753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile12
Maximum112
Range112
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.800575316
Coefficient of variation (CV)1.408966915
Kurtosis31.07724065
Mean3.407159717
Median Absolute Deviation (MAD)2
Skewness3.452469545
Sum69288
Variance23.04552336
MonotonicityNot monotonic
2021-11-29T11:22:27.803100image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
07759
38.2%
12118
 
10.4%
21699
 
8.4%
31494
 
7.3%
41331
 
6.5%
51179
 
5.8%
6914
 
4.5%
7798
 
3.9%
8652
 
3.2%
9541
 
2.7%
Other values (42)1851
 
9.1%
ValueCountFrequency (%)
07759
38.2%
12118
 
10.4%
21699
 
8.4%
31494
 
7.3%
41331
 
6.5%
51179
 
5.8%
6914
 
4.5%
7798
 
3.9%
8652
 
3.2%
9541
 
2.7%
ValueCountFrequency (%)
1121
 
< 0.1%
831
 
< 0.1%
821
 
< 0.1%
542
< 0.1%
521
 
< 0.1%
491
 
< 0.1%
482
< 0.1%
472
< 0.1%
442
< 0.1%
433
< 0.1%

SaO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct48
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.925649095
Minimum0
Maximum89
Zeros12373
Zeros (%)60.8%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:27.904269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile10
Maximum89
Range89
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.911635103
Coefficient of variation (CV)2.031333285
Kurtosis47.10785228
Mean1.925649095
Median Absolute Deviation (MAD)0
Skewness4.636342735
Sum39160
Variance15.30088918
MonotonicityNot monotonic
2021-11-29T11:22:28.073553image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
012373
60.8%
11690
 
8.3%
21403
 
6.9%
4908
 
4.5%
3844
 
4.2%
5617
 
3.0%
6552
 
2.7%
7384
 
1.9%
8307
 
1.5%
9240
 
1.2%
Other values (38)1018
 
5.0%
ValueCountFrequency (%)
012373
60.8%
11690
 
8.3%
21403
 
6.9%
3844
 
4.2%
4908
 
4.5%
5617
 
3.0%
6552
 
2.7%
7384
 
1.9%
8307
 
1.5%
9240
 
1.2%
ValueCountFrequency (%)
891
< 0.1%
831
< 0.1%
681
< 0.1%
631
< 0.1%
601
< 0.1%
561
< 0.1%
551
< 0.1%
471
< 0.1%
462
< 0.1%
442
< 0.1%

AST
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct26
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5812352478
Minimum0
Maximum71
Zeros14443
Zeros (%)71.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:28.162541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum71
Range71
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.459826751
Coefficient of variation (CV)2.511593638
Kurtosis308.277976
Mean0.5812352478
Median Absolute Deviation (MAD)0
Skewness10.13997827
Sum11820
Variance2.131094142
MonotonicityNot monotonic
2021-11-29T11:22:28.245902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
014443
71.0%
13234
 
15.9%
21582
 
7.8%
3357
 
1.8%
4328
 
1.6%
6110
 
0.5%
5104
 
0.5%
741
 
0.2%
841
 
0.2%
1020
 
0.1%
Other values (16)76
 
0.4%
ValueCountFrequency (%)
014443
71.0%
13234
 
15.9%
21582
 
7.8%
3357
 
1.8%
4328
 
1.6%
5104
 
0.5%
6110
 
0.5%
741
 
0.2%
841
 
0.2%
920
 
0.1%
ValueCountFrequency (%)
711
< 0.1%
301
< 0.1%
251
< 0.1%
231
< 0.1%
222
< 0.1%
211
< 0.1%
202
< 0.1%
181
< 0.1%
172
< 0.1%
162
< 0.1%

BUN
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct45
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.170535012
Minimum0
Maximum79
Zeros427
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:28.344126image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q34
95-th percentile8
Maximum79
Range79
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.810082173
Coefficient of variation (CV)0.8863116674
Kurtosis58.24365923
Mean3.170535012
Median Absolute Deviation (MAD)1
Skewness4.997278866
Sum64476
Variance7.896561818
MonotonicityNot monotonic
2021-11-29T11:22:28.440642image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
26092
30.0%
34083
20.1%
13800
18.7%
42413
 
11.9%
51024
 
5.0%
6964
 
4.7%
0427
 
2.1%
8424
 
2.1%
7368
 
1.8%
9171
 
0.8%
Other values (35)570
 
2.8%
ValueCountFrequency (%)
0427
 
2.1%
13800
18.7%
26092
30.0%
34083
20.1%
42413
 
11.9%
51024
 
5.0%
6964
 
4.7%
7368
 
1.8%
8424
 
2.1%
9171
 
0.8%
ValueCountFrequency (%)
791
< 0.1%
471
< 0.1%
451
< 0.1%
441
< 0.1%
421
< 0.1%
401
< 0.1%
391
< 0.1%
382
< 0.1%
371
< 0.1%
361
< 0.1%

Alkalinephos
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct26
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5670731707
Minimum0
Maximum69
Zeros14633
Zeros (%)72.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:28.533129image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum69
Range69
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.462127618
Coefficient of variation (CV)2.578375585
Kurtosis285.9869959
Mean0.5670731707
Median Absolute Deviation (MAD)0
Skewness10.02332193
Sum11532
Variance2.137817172
MonotonicityNot monotonic
2021-11-29T11:22:28.614889image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
014633
72.0%
13124
 
15.4%
21518
 
7.5%
3349
 
1.7%
4327
 
1.6%
6105
 
0.5%
5101
 
0.5%
746
 
0.2%
837
 
0.2%
1019
 
0.1%
Other values (16)77
 
0.4%
ValueCountFrequency (%)
014633
72.0%
13124
 
15.4%
21518
 
7.5%
3349
 
1.7%
4327
 
1.6%
5101
 
0.5%
6105
 
0.5%
746
 
0.2%
837
 
0.2%
918
 
0.1%
ValueCountFrequency (%)
691
< 0.1%
311
< 0.1%
301
< 0.1%
251
< 0.1%
231
< 0.1%
222
< 0.1%
202
< 0.1%
182
< 0.1%
171
< 0.1%
162
< 0.1%

Calcium
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.933418568
Minimum0
Maximum58
Zeros3789
Zeros (%)18.6%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:28.705639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum58
Range58
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.954332929
Coefficient of variation (CV)1.010817296
Kurtosis49.97311838
Mean1.933418568
Median Absolute Deviation (MAD)1
Skewness3.993411826
Sum39318
Variance3.819417199
MonotonicityNot monotonic
2021-11-29T11:22:28.785706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
15931
29.2%
25136
25.3%
03789
18.6%
32912
14.3%
41219
 
6.0%
5547
 
2.7%
6281
 
1.4%
7153
 
0.8%
8114
 
0.6%
960
 
0.3%
Other values (17)194
 
1.0%
ValueCountFrequency (%)
03789
18.6%
15931
29.2%
25136
25.3%
32912
14.3%
41219
 
6.0%
5547
 
2.7%
6281
 
1.4%
7153
 
0.8%
8114
 
0.6%
960
 
0.3%
ValueCountFrequency (%)
581
 
< 0.1%
281
 
< 0.1%
261
 
< 0.1%
233
 
< 0.1%
221
 
< 0.1%
211
 
< 0.1%
203
 
< 0.1%
197
< 0.1%
188
< 0.1%
173
 
< 0.1%

Chloride
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct43
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.234510228
Minimum0
Maximum76
Zeros542
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:28.879199image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q34
95-th percentile8
Maximum76
Range76
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.006579301
Coefficient of variation (CV)0.9295315484
Kurtosis50.6542188
Mean3.234510228
Median Absolute Deviation (MAD)1
Skewness4.864262822
Sum65777
Variance9.039519091
MonotonicityNot monotonic
2021-11-29T11:22:28.972335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
25988
29.4%
33912
19.2%
13856
19.0%
42258
 
11.1%
51083
 
5.3%
6973
 
4.8%
0542
 
2.7%
8439
 
2.2%
7405
 
2.0%
9199
 
1.0%
Other values (33)681
 
3.3%
ValueCountFrequency (%)
0542
 
2.7%
13856
19.0%
25988
29.4%
33912
19.2%
42258
 
11.1%
51083
 
5.3%
6973
 
4.8%
7405
 
2.0%
8439
 
2.2%
9199
 
1.0%
ValueCountFrequency (%)
761
 
< 0.1%
481
 
< 0.1%
452
 
< 0.1%
442
 
< 0.1%
425
< 0.1%
401
 
< 0.1%
391
 
< 0.1%
381
 
< 0.1%
374
< 0.1%
361
 
< 0.1%

Creatinine
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct28
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.580989378
Minimum0
Maximum79
Zeros461
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:29.065771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile6
Maximum79
Range79
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9986301
Coefficient of variation (CV)0.7743658756
Kurtosis123.4574129
Mean2.580989378
Median Absolute Deviation (MAD)1
Skewness5.815561521
Sum52487
Variance3.994522277
MonotonicityNot monotonic
2021-11-29T11:22:29.149895image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
26728
33.1%
14900
24.1%
34461
21.9%
41913
 
9.4%
5808
 
4.0%
0461
 
2.3%
6383
 
1.9%
7211
 
1.0%
8125
 
0.6%
986
 
0.4%
Other values (18)260
 
1.3%
ValueCountFrequency (%)
0461
 
2.3%
14900
24.1%
26728
33.1%
34461
21.9%
41913
 
9.4%
5808
 
4.0%
6383
 
1.9%
7211
 
1.0%
8125
 
0.6%
986
 
0.4%
ValueCountFrequency (%)
791
 
< 0.1%
272
 
< 0.1%
251
 
< 0.1%
242
 
< 0.1%
231
 
< 0.1%
224
< 0.1%
213
 
< 0.1%
205
< 0.1%
199
< 0.1%
189
< 0.1%

Bilirubin_direct
Real number (ℝ≥0)

ZEROS

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05812352478
Minimum0
Maximum13
Zeros19750
Zeros (%)97.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:29.231511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4435865402
Coefficient of variation (CV)7.631790085
Kurtosis215.0285965
Mean0.05812352478
Median Absolute Deviation (MAD)0
Skewness12.54955973
Sum1182
Variance0.1967690186
MonotonicityNot monotonic
2021-11-29T11:22:29.311224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
019750
97.1%
1310
 
1.5%
2155
 
0.8%
344
 
0.2%
436
 
0.2%
513
 
0.1%
89
 
< 0.1%
68
 
< 0.1%
75
 
< 0.1%
103
 
< 0.1%
Other values (3)3
 
< 0.1%
ValueCountFrequency (%)
019750
97.1%
1310
 
1.5%
2155
 
0.8%
344
 
0.2%
436
 
0.2%
513
 
0.1%
68
 
< 0.1%
75
 
< 0.1%
89
 
< 0.1%
103
 
< 0.1%
ValueCountFrequency (%)
131
 
< 0.1%
121
 
< 0.1%
111
 
< 0.1%
103
 
< 0.1%
89
 
< 0.1%
75
 
< 0.1%
68
 
< 0.1%
513
 
0.1%
436
0.2%
344
0.2%

Glucose
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct56
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.752950433
Minimum0
Maximum124
Zeros407
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:29.401996image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q36
95-th percentile14
Maximum124
Range124
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.993237733
Coefficient of variation (CV)1.050555398
Kurtosis33.74211321
Mean4.752950433
Median Absolute Deviation (MAD)2
Skewness3.74680667
Sum96656
Variance24.93242306
MonotonicityNot monotonic
2021-11-29T11:22:29.581962image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24225
20.8%
13357
16.5%
33190
15.7%
42176
10.7%
51502
 
7.4%
61098
 
5.4%
7856
 
4.2%
8608
 
3.0%
9504
 
2.5%
0407
 
2.0%
Other values (46)2413
11.9%
ValueCountFrequency (%)
0407
 
2.0%
13357
16.5%
24225
20.8%
33190
15.7%
42176
10.7%
51502
 
7.4%
61098
 
5.4%
7856
 
4.2%
8608
 
3.0%
9504
 
2.5%
ValueCountFrequency (%)
1241
< 0.1%
871
< 0.1%
711
< 0.1%
691
< 0.1%
591
< 0.1%
581
< 0.1%
552
< 0.1%
491
< 0.1%
481
< 0.1%
461
< 0.1%

Lactate
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct42
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.334726593
Minimum0
Maximum50
Zeros12603
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:29.681680image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7
Maximum50
Range50
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.954573839
Coefficient of variation (CV)2.213617271
Kurtosis39.13051119
Mean1.334726593
Median Absolute Deviation (MAD)0
Skewness4.859452674
Sum27143
Variance8.729506569
MonotonicityNot monotonic
2021-11-29T11:22:29.781868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
012603
62.0%
12643
 
13.0%
21774
 
8.7%
3823
 
4.0%
4744
 
3.7%
6375
 
1.8%
5352
 
1.7%
7215
 
1.1%
8211
 
1.0%
10124
 
0.6%
Other values (32)472
 
2.3%
ValueCountFrequency (%)
012603
62.0%
12643
 
13.0%
21774
 
8.7%
3823
 
4.0%
4744
 
3.7%
5352
 
1.7%
6375
 
1.8%
7215
 
1.1%
8211
 
1.0%
985
 
0.4%
ValueCountFrequency (%)
502
< 0.1%
471
 
< 0.1%
461
 
< 0.1%
431
 
< 0.1%
421
 
< 0.1%
381
 
< 0.1%
361
 
< 0.1%
354
< 0.1%
341
 
< 0.1%
331
 
< 0.1%

Magnesium
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct43
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.023259245
Minimum0
Maximum80
Zeros1388
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:29.882612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile8
Maximum80
Range80
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.906797426
Coefficient of variation (CV)0.9614780575
Kurtosis52.26906207
Mean3.023259245
Median Absolute Deviation (MAD)1
Skewness4.668587162
Sum61481
Variance8.449471275
MonotonicityNot monotonic
2021-11-29T11:22:29.975400image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
25564
27.4%
14078
20.1%
33388
16.7%
42493
12.3%
01388
 
6.8%
6982
 
4.8%
5972
 
4.8%
8406
 
2.0%
7303
 
1.5%
10191
 
0.9%
Other values (33)571
 
2.8%
ValueCountFrequency (%)
01388
 
6.8%
14078
20.1%
25564
27.4%
33388
16.7%
42493
12.3%
5972
 
4.8%
6982
 
4.8%
7303
 
1.5%
8406
 
2.0%
9155
 
0.8%
ValueCountFrequency (%)
801
 
< 0.1%
441
 
< 0.1%
422
< 0.1%
402
< 0.1%
393
< 0.1%
381
 
< 0.1%
372
< 0.1%
361
 
< 0.1%
351
 
< 0.1%
331
 
< 0.1%

Phosphate
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct28
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.96184107
Minimum0
Maximum76
Zeros3650
Zeros (%)17.9%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:30.066742image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum76
Range76
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.013727034
Coefficient of variation (CV)1.026447588
Kurtosis106.0632232
Mean1.96184107
Median Absolute Deviation (MAD)1
Skewness5.245133115
Sum39896
Variance4.055096566
MonotonicityNot monotonic
2021-11-29T11:22:30.148802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
15920
29.1%
25252
25.8%
03650
17.9%
32911
14.3%
41218
 
6.0%
5559
 
2.7%
6282
 
1.4%
7161
 
0.8%
8108
 
0.5%
970
 
0.3%
Other values (18)205
 
1.0%
ValueCountFrequency (%)
03650
17.9%
15920
29.1%
25252
25.8%
32911
14.3%
41218
 
6.0%
5559
 
2.7%
6282
 
1.4%
7161
 
0.8%
8108
 
0.5%
970
 
0.3%
ValueCountFrequency (%)
761
 
< 0.1%
281
 
< 0.1%
261
 
< 0.1%
251
 
< 0.1%
232
 
< 0.1%
222
 
< 0.1%
211
 
< 0.1%
203
 
< 0.1%
199
< 0.1%
186
< 0.1%

Potassium
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct51
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.220889064
Minimum0
Maximum76
Zeros433
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:30.247109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q35
95-th percentile11
Maximum76
Range76
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.848877268
Coefficient of variation (CV)0.9118641144
Kurtosis28.11753441
Mean4.220889064
Median Absolute Deviation (MAD)1
Skewness3.653350215
Sum85836
Variance14.81385622
MonotonicityNot monotonic
2021-11-29T11:22:30.347377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24445
21.9%
33282
16.1%
12999
14.7%
42675
13.2%
51565
 
7.7%
61346
 
6.6%
7802
 
3.9%
8765
 
3.8%
9463
 
2.3%
10442
 
2.2%
Other values (41)1552
 
7.6%
ValueCountFrequency (%)
0433
 
2.1%
12999
14.7%
24445
21.9%
33282
16.1%
42675
13.2%
51565
 
7.7%
61346
 
6.6%
7802
 
3.9%
8765
 
3.8%
9463
 
2.3%
ValueCountFrequency (%)
761
 
< 0.1%
611
 
< 0.1%
591
 
< 0.1%
491
 
< 0.1%
481
 
< 0.1%
462
< 0.1%
453
< 0.1%
442
< 0.1%
431
 
< 0.1%
422
< 0.1%

Bilirubin_total
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct19
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4766424076
Minimum0
Maximum73
Zeros14566
Zeros (%)71.6%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:30.440344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum73
Range73
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.172442052
Coefficient of variation (CV)2.459793828
Kurtosis742.438579
Mean0.4766424076
Median Absolute Deviation (MAD)0
Skewness14.99521428
Sum9693
Variance1.374620366
MonotonicityNot monotonic
2021-11-29T11:22:30.516719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
014566
71.6%
13814
 
18.8%
21154
 
5.7%
3394
 
1.9%
4160
 
0.8%
590
 
0.4%
656
 
0.3%
745
 
0.2%
818
 
0.1%
910
 
< 0.1%
Other values (9)29
 
0.1%
ValueCountFrequency (%)
014566
71.6%
13814
 
18.8%
21154
 
5.7%
3394
 
1.9%
4160
 
0.8%
590
 
0.4%
656
 
0.3%
745
 
0.2%
818
 
0.1%
910
 
< 0.1%
ValueCountFrequency (%)
731
 
< 0.1%
181
 
< 0.1%
171
 
< 0.1%
152
 
< 0.1%
143
 
< 0.1%
131
 
< 0.1%
127
< 0.1%
117
< 0.1%
106
< 0.1%
910
< 0.1%

TroponinI
Real number (ℝ≥0)

ZEROS

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04745279308
Minimum0
Maximum11
Zeros19847
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:30.598053image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3547567835
Coefficient of variation (CV)7.47599373
Kurtosis141.305671
Mean0.04745279308
Median Absolute Deviation (MAD)0
Skewness10.17672372
Sum965
Variance0.1258523754
MonotonicityNot monotonic
2021-11-29T11:22:30.668162image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
019847
97.6%
1218
 
1.1%
2141
 
0.7%
386
 
0.4%
427
 
0.1%
511
 
0.1%
63
 
< 0.1%
71
 
< 0.1%
81
 
< 0.1%
111
 
< 0.1%
ValueCountFrequency (%)
019847
97.6%
1218
 
1.1%
2141
 
0.7%
386
 
0.4%
427
 
0.1%
511
 
0.1%
63
 
< 0.1%
71
 
< 0.1%
81
 
< 0.1%
111
 
< 0.1%
ValueCountFrequency (%)
111
 
< 0.1%
81
 
< 0.1%
71
 
< 0.1%
63
 
< 0.1%
511
 
0.1%
427
 
0.1%
386
 
0.4%
2141
 
0.7%
1218
 
1.1%
019847
97.6%

Hct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct52
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.576022817
Minimum0
Maximum114
Zeros364
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:30.755567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q36
95-th percentile12
Maximum114
Range114
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.070055744
Coefficient of variation (CV)0.8894308239
Kurtosis44.11510478
Mean4.576022817
Median Absolute Deviation (MAD)2
Skewness3.938058593
Sum93058
Variance16.56535376
MonotonicityNot monotonic
2021-11-29T11:22:30.855202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24079
20.1%
33044
15.0%
12607
12.8%
42594
12.8%
51872
9.2%
61618
 
8.0%
71025
 
5.0%
8817
 
4.0%
9524
 
2.6%
10397
 
2.0%
Other values (42)1759
8.6%
ValueCountFrequency (%)
0364
 
1.8%
12607
12.8%
24079
20.1%
33044
15.0%
42594
12.8%
51872
9.2%
61618
 
8.0%
71025
 
5.0%
8817
 
4.0%
9524
 
2.6%
ValueCountFrequency (%)
1141
< 0.1%
611
< 0.1%
601
< 0.1%
591
< 0.1%
491
< 0.1%
481
< 0.1%
472
< 0.1%
462
< 0.1%
442
< 0.1%
431
< 0.1%

Hgb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct41
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.433369394
Minimum0
Maximum102
Zeros507
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:30.954589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile9
Maximum102
Range102
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.090868039
Coefficient of variation (CV)0.9002433715
Kurtosis70.7239233
Mean3.433369394
Median Absolute Deviation (MAD)1
Skewness4.710393169
Sum69821
Variance9.553465234
MonotonicityNot monotonic
2021-11-29T11:22:31.124221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
25692
28.0%
13750
18.4%
33468
17.1%
42376
11.7%
51262
 
6.2%
61090
 
5.4%
7582
 
2.9%
0507
 
2.5%
8493
 
2.4%
9292
 
1.4%
Other values (31)824
 
4.1%
ValueCountFrequency (%)
0507
 
2.5%
13750
18.4%
25692
28.0%
33468
17.1%
42376
11.7%
51262
 
6.2%
61090
 
5.4%
7582
 
2.9%
8493
 
2.4%
9292
 
1.4%
ValueCountFrequency (%)
1021
 
< 0.1%
531
 
< 0.1%
441
 
< 0.1%
381
 
< 0.1%
373
< 0.1%
351
 
< 0.1%
344
< 0.1%
334
< 0.1%
321
 
< 0.1%
312
< 0.1%

PTT
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct32
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.883654603
Minimum0
Maximum105
Zeros4496
Zeros (%)22.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:31.215096image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile6
Maximum105
Range105
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.236174932
Coefficient of variation (CV)1.187147011
Kurtosis241.2853033
Mean1.883654603
Median Absolute Deviation (MAD)1
Skewness7.745164115
Sum38306
Variance5.000478328
MonotonicityNot monotonic
2021-11-29T11:22:31.303535image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
16472
31.8%
04496
22.1%
24373
21.5%
32130
 
10.5%
41114
 
5.5%
5697
 
3.4%
6394
 
1.9%
7253
 
1.2%
8128
 
0.6%
978
 
0.4%
Other values (22)201
 
1.0%
ValueCountFrequency (%)
04496
22.1%
16472
31.8%
24373
21.5%
32130
 
10.5%
41114
 
5.5%
5697
 
3.4%
6394
 
1.9%
7253
 
1.2%
8128
 
0.6%
978
 
0.4%
ValueCountFrequency (%)
1051
 
< 0.1%
311
 
< 0.1%
301
 
< 0.1%
294
< 0.1%
281
 
< 0.1%
271
 
< 0.1%
261
 
< 0.1%
242
< 0.1%
232
< 0.1%
224
< 0.1%

WBC
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct39
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.918371361
Minimum0
Maximum83
Zeros625
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:31.396491image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q34
95-th percentile7
Maximum83
Range83
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.575045233
Coefficient of variation (CV)0.8823569431
Kurtosis74.7842383
Mean2.918371361
Median Absolute Deviation (MAD)1
Skewness5.177468517
Sum59348
Variance6.630857952
MonotonicityNot monotonic
2021-11-29T11:22:31.485624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
26572
32.3%
14301
21.1%
33626
17.8%
42210
 
10.9%
5920
 
4.5%
6852
 
4.2%
0625
 
3.1%
8305
 
1.5%
7305
 
1.5%
9154
 
0.8%
Other values (29)466
 
2.3%
ValueCountFrequency (%)
0625
 
3.1%
14301
21.1%
26572
32.3%
33626
17.8%
42210
 
10.9%
5920
 
4.5%
6852
 
4.2%
7305
 
1.5%
8305
 
1.5%
9154
 
0.8%
ValueCountFrequency (%)
831
< 0.1%
521
< 0.1%
372
< 0.1%
351
< 0.1%
341
< 0.1%
332
< 0.1%
321
< 0.1%
311
< 0.1%
301
< 0.1%
292
< 0.1%

Fibrinogen
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2965184894
Minimum0
Maximum90
Zeros17769
Zeros (%)87.4%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:31.572582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum90
Range90
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.368477776
Coefficient of variation (CV)4.615151585
Kurtosis985.723149
Mean0.2965184894
Median Absolute Deviation (MAD)0
Skewness20.20727704
Sum6030
Variance1.872731424
MonotonicityNot monotonic
2021-11-29T11:22:31.653480image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
017769
87.4%
11397
 
6.9%
2577
 
2.8%
3165
 
0.8%
4150
 
0.7%
677
 
0.4%
559
 
0.3%
736
 
0.2%
824
 
0.1%
914
 
0.1%
Other values (17)68
 
0.3%
ValueCountFrequency (%)
017769
87.4%
11397
 
6.9%
2577
 
2.8%
3165
 
0.8%
4150
 
0.7%
559
 
0.3%
677
 
0.4%
736
 
0.2%
824
 
0.1%
914
 
0.1%
ValueCountFrequency (%)
901
 
< 0.1%
321
 
< 0.1%
301
 
< 0.1%
242
 
< 0.1%
231
 
< 0.1%
221
 
< 0.1%
211
 
< 0.1%
194
< 0.1%
185
< 0.1%
175
< 0.1%

Platelets
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct32
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.532405586
Minimum0
Maximum109
Zeros585
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:31.742301image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile6
Maximum109
Range109
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.091215304
Coefficient of variation (CV)0.8257821398
Kurtosis353.1509342
Mean2.532405586
Median Absolute Deviation (MAD)1
Skewness9.638136102
Sum51499
Variance4.373181447
MonotonicityNot monotonic
2021-11-29T11:22:31.831785image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
27050
34.7%
14962
24.4%
34165
20.5%
41728
 
8.5%
5744
 
3.7%
0585
 
2.9%
6409
 
2.0%
7221
 
1.1%
8141
 
0.7%
980
 
0.4%
Other values (22)251
 
1.2%
ValueCountFrequency (%)
0585
 
2.9%
14962
24.4%
27050
34.7%
34165
20.5%
41728
 
8.5%
5744
 
3.7%
6409
 
2.0%
7221
 
1.1%
8141
 
0.7%
980
 
0.4%
ValueCountFrequency (%)
1091
< 0.1%
351
< 0.1%
331
< 0.1%
321
< 0.1%
311
< 0.1%
282
< 0.1%
262
< 0.1%
242
< 0.1%
231
< 0.1%
221
< 0.1%

Age
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:31.929722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:22:32.031397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

Gender
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:32.138372image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:22:32.240505image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

Unit1
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct172
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.86870574
Minimum0
Maximum336
Zeros9522
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:32.347511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16
Q339
95-th percentile54
Maximum336
Range336
Interquartile range (IQR)39

Descriptive statistics

Standard deviation23.44210331
Coefficient of variation (CV)1.179850546
Kurtosis14.03526987
Mean19.86870574
Median Absolute Deviation (MAD)16
Skewness2.096025958
Sum404050
Variance549.5322077
MonotonicityNot monotonic
2021-11-29T11:22:32.443500image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09522
46.8%
36364
 
1.8%
39341
 
1.7%
37337
 
1.7%
40327
 
1.6%
41327
 
1.6%
38321
 
1.6%
43321
 
1.6%
42315
 
1.5%
44311
 
1.5%
Other values (162)7850
38.6%
ValueCountFrequency (%)
09522
46.8%
870
 
0.3%
965
 
0.3%
1050
 
0.2%
1153
 
0.3%
1269
 
0.3%
1377
 
0.4%
14101
 
0.5%
15129
 
0.6%
16154
 
0.8%
ValueCountFrequency (%)
3362
< 0.1%
2971
< 0.1%
2861
< 0.1%
2771
< 0.1%
2711
< 0.1%
2651
< 0.1%
2561
< 0.1%
2432
< 0.1%
2381
< 0.1%
2351
< 0.1%

Unit2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct172
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.86870574
Minimum0
Maximum336
Zeros9522
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:32.621198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16
Q339
95-th percentile54
Maximum336
Range336
Interquartile range (IQR)39

Descriptive statistics

Standard deviation23.44210331
Coefficient of variation (CV)1.179850546
Kurtosis14.03526987
Mean19.86870574
Median Absolute Deviation (MAD)16
Skewness2.096025958
Sum404050
Variance549.5322077
MonotonicityNot monotonic
2021-11-29T11:22:32.716479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09522
46.8%
36364
 
1.8%
39341
 
1.7%
37337
 
1.7%
40327
 
1.6%
41327
 
1.6%
38321
 
1.6%
43321
 
1.6%
42315
 
1.5%
44311
 
1.5%
Other values (162)7850
38.6%
ValueCountFrequency (%)
09522
46.8%
870
 
0.3%
965
 
0.3%
1050
 
0.2%
1153
 
0.3%
1269
 
0.3%
1377
 
0.4%
14101
 
0.5%
15129
 
0.6%
16154
 
0.8%
ValueCountFrequency (%)
3362
< 0.1%
2971
< 0.1%
2861
< 0.1%
2771
< 0.1%
2711
< 0.1%
2651
< 0.1%
2561
< 0.1%
2432
< 0.1%
2381
< 0.1%
2351
< 0.1%

HospAdmTime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct229
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85754327
Minimum0
Maximum336
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:32.818746image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range336
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30927338
Coefficient of variation (CV)0.5741297956
Kurtosis40.48672306
Mean38.85754327
Median Absolute Deviation (MAD)11
Skewness4.702745502
Sum790207
Variance497.7036785
MonotonicityNot monotonic
2021-11-29T11:22:32.918971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (219)14080
69.2%
ValueCountFrequency (%)
01
 
< 0.1%
8123
0.6%
9122
0.6%
1095
 
0.5%
11114
0.6%
12121
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

ICULOS
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:33.026587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:22:33.127148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

SepsisLabel
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:33.234207image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:22:33.334609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

Sepsis
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:33.441211image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:22:33.541471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

Hours
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:33.648207image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:22:33.748744image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

Interactions

2021-11-29T11:22:23.252507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:11.327677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:11.595738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:11.940590image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.214571image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.482677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.755213image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.027591image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.300195image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.572268image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.914140image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.173027image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.444917image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.716420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.984254image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.243565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.518548image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.799916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.153840image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.427361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.706484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.992805image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.267833image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.541066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.806904image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.165690image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.445209image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.725293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.009923image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.274813image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.539544image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.804667image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.143205image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.400947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.663727image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.931803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.210991image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.491411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.770628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.050845image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.407754image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.688307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.972122image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:23.346778image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:11.418113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:11.687025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.032299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.304937image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.574174image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.846867image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.119088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.391760image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.662334image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.001125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.264108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.535665image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.805894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.071540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.336411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.613421image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.967446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.245999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.520930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.802444image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.084983image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.359950image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.630343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.902427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.259509image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.538993image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.820789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.099028image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.363834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.628365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.893360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.230005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.488998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.753588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.025842image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.305367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.585313image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.864233image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.219725image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.501934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.783535image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:23.066573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:23.439677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:11.506979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:11.850740image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.123482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.393769image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.664870image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:12.937280image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.210047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.482058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:13.751311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.087265image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.354310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.626209image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:14.895583image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.157291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.427506image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:15.706837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.060583image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.336645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.613798image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:16.898002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.176498image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.450654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:17.718658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.071066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.352481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.631945image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:18.914413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.186982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.451838image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.716954image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:19.981398image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.315669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.576148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:20.842771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.118502image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.398479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.678027image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:21.957623image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.313809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.595199image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:22.877757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:22:23.159492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-11-29T11:22:33.970224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T11:22:34.322008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T11:22:34.673864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Missing values

2021-11-29T11:22:23.681764image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-11-29T11:22:24.788181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
0149441042420500724764121222020222102202025454005454545454
122222615221519001000001011101011100110101232323232323232323
2345441645454245023732003033303033400432303484848484848484848
342727626261426022032302012203021300212102292929292929292929
45242192417021003000033333303033330332303484848484848484848
5616165151506011211001001103100100110101171717171717171717
67444414444443440561355016166606266610655506454545454545454545
783836113838383801411014800110411607107412006606034040004040404040
892382381122382382252380472177474712019017191903624181835003327141761925825800258258258258258
91023232123232323042744302003203110300321202232323232323232323

Last rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
203262063420202020202020071587502001207010600422102202020202020202020
2032720635404010294029390230210020121022212002222014242004242424242
203282063643431243434343045672325207206040710951502434343434343434343
20329206371401403684140841410272733271500250132713013725132700141421407142142142142142142142142142
2033020638404011334033400030000030131010313003313014141004141414141
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